[R-SIG-Finance] Is it possible to import residuals of mean.model into variance.model in rugarch package or others?
samuelsangchy at hotmail.com
Fri Dec 28 08:31:36 CET 2012
Hi, Alexios. Thanks a lot for your suggestions. I have tried the method and
successfully pass mean.model residuals to variance.model as data and part of
external.variable. Could you give me some further guidances for my several
new problems listed below? I ask for apology if some of them seem shalow. I
am a new fish for R and i am learning and trying hard.
Firstly, i don't understand how to use the 'setstart=' and 'setbounds'
methods on the spec as you had mentioned. I can only find them in
'uGARCHspec-class' in reference manual, yet it doesn't show how to put them
in spec correctly. When i put
'setbounds=list("alpha1"=c(0,1),"beta1"=c(0,1))' into spec and run it, R
reflects 'setbounds=list("alpha1"=c(0,1),"beta1"=c(0,1)) is of no use'. Does
'set.start' equals to 'start.pars=list()'? Is there a principle to follow
when i provide starting values for regressor parameters?
Secondly, i got 'ugarchfit-->warning: solver failer to converge' problems
when i use all solvers of rugarch package to fit my model. It has been
confusing me how to set the 'solver.control' or 'fix.control' options
properly to get a convergent result.
In topic "rugarch package "Warning Message" for GARCH-Normal" presented by
nserdar, you provided seven suggestions to deal with 'warning: failed to
invert hessian' in order of likely importance. Though the warning i got is
different from his, i still want to ask some questions about several of the
1. Set tol<delta (in solver.control).
Q:what are tol and delta, where can i find more details about
2. Use scaling (in fit.control).
Q:Is it correct to write 'scaling=1' or 'scaling=TRUE' to make scaling
3. Set stationarity to FALSE (sometimes this creates problems with the
solver for some boundary cases).
4. Use an alternate solver(s) (there are many now included).
5. Change the default solver parameters.
6. Use starting values.
Q:How to change default solver parameters or use starting values
properly, is there a principle to follow or other papers or books i need to
7. Check your data for extreme outliers or numbers of zeros.
Q:In the matrix of my exteral.variable, there are quite a lot of zeros.
Does that affect the convergence?
Here is part of my code:
#external.regressors matrix 'DummyRessquaar' subdivide the asymetrique part
(1: In .solnpsolver(pars, fun, Ifn, ILB, IUB, control, LB, UB, arglist) :
rugarch-->warning: no convergence...)
2: In .sgarchfit(spec = spec, data = data, out.sample = out.sample, :
ugarchfit-->warning: solver failer to converge.
Thanks for your kind and patience.
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